https://github.com/azshue/AdvBN
Recognizing Instagram Filtered Images with Feature De-stylization
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
What is Human Pose Estimation? Human pose estimation is the process of estimating the configuration of the body (pose) from a single, typically monocular, image. Background. Human pose estimation is one of the key problems in computer vision that has been studied for well over 15 years. The reason for its importance is the abundance of applications that can benefit from such a technology. For example, human pose estimation allows for higher-level reasoning in the context of human-computer interaction and activity recognition; it is also one of the basic building blocks for marker-less motion capture (MoCap) technology. MoCap technology is useful for applications ranging from character animation to clinical analysis of gait pathologies.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Recognizing Instagram Filtered Images with Feature De-stylization
Associative Embedding: End-to-End Learning for Joint Detection and Grouping
Deep High-Resolution Representation Learning for Human Pose Estimation
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data
Attention-based Stylisation for Exemplar Image Colourisation
STARD: A Chinese Statute Retrieval Dataset with Real Queries Issued by Non-professionals
Style Transfer by Relaxed Optimal Transport and Self-Similarity
Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context
Inferring Which Medical Treatments Work from Reports of Clinical Trials
Learning to Reason for Text Generation from Scientific Tables
Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization
Accurate and scalable social recommendation using mixed-membership stochastic block models
Exploring the structure of a real-time, arbitrary neural artistic stylization network
ChemGrapher: Optical Graph Recognition of Chemical Compounds by Deep Learning
Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
Bringing Structure into Summaries: a Faceted Summarization Dataset for Long Scientific Documents
ANER: Arabic and Arabizi Named Entity Recognition using Transformer-Based Approach
Newsroom: A Dataset of 1.3 Million Summaries with Diverse Extractive Strategies
BVS Corpus: A Multilingual Parallel Corpus of Biomedical Scientific Texts
Near-Optimal Representation Learning for Hierarchical Reinforcement Learning
CAIL2018: A Large-Scale Legal Dataset for Judgment Prediction
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.